Opioid prescribing exceeds consumption following common surgical oncology procedures

Efficacy of a password-protected, pill-dispensing device with mail return capacity to enhance disposal of unused opioids after cancer surgery

BACKGROUND

Opioid misuse is a public health crisis, and unused postoperative opioids are an important source. Although 70% of pills prescribed go unused, only 9% are discarded. This study evaluated whether an inexpensive pill-dispensing device with mail return capacity could enhance disposal of unused opioids after cancer surgery.

METHODS

A prospective pilot study was conducted among adult patients who underwent major cancer-related surgery. Patients received opioid prescriptions in a mechanical device (Addinex) linked to a smartphone application (app). The app provided passwords on a prescriber-defined schedule. Patients could enter a password into the device and receive a pill if the prescribed time had elapsed. Patients were instructed to return the device and any unused pills in a disposal mailer. The primary end point was feasibility of device return, defined as ≥50% of patients returning the device within 6 weeks of surgery. Also explored was total pill use and return as well as patient satisfaction.

RESULTS

Among 30 patients enrolled, the majority (n = 24, 80%) returned the device, and 17 (57%) returned it within 6 weeks of surgery. In total, 567 opioid pills were prescribed and 170 (30%) were used. Of 397 excess pills, 332 (84% of unused pills, 59% of all pills prescribed) were disposed of by mail. Among 19 patients who obtained opioids from the device, most (n = 14, 74%) felt the benefits of the device justified the added steps involved.

CONCLUSIONS

Use of an inexpensive pill-dispensing device with mail return capacity is a feasible strategy to enhance disposal of unused postoperative opioids.

How Much Pain Will I Have After Surgery? A Preoperative Nomogram to Predict Acute Pain Following Mastectomy

INTRODUCTION

Acute postoperative pain affects time to opioid cessation and quality of life, and is associated with chronic pain. Effective screening tools are needed to identify patients at increased risk of experiencing more severe acute postoperative pain, and who may benefit from multimodal analgesia and early pain management referral. In this study, we develop a nomogram to preoperatively identify patients at high risk of moderate-severe pain following mastectomy.

METHODS

Demographic, psychosocial, and clinical variables were retrospectively assessed in 1195 consecutive patients who underwent mastectomy from January 2019 to December 2020 and had pain scores available from a post-discharge questionnaire. We examined pain severity on postoperative days 1-5, with moderate-severe pain as the outcome of interest. Multivariable logistic regression was performed to identify variables associated with moderate-severe pain in a training cohort of 956 patients. The final model was determined using the Akaike information criterion. A nomogram was constructed using this model, which also included a priori selected clinically relevant variables. Internal validation was performed in the remaining cohort of 239 patients.

RESULTS

In the training cohort, 297 patients reported no-mild pain and 659 reported moderate-severe pain. High body mass index (p = 0.042), preoperative Distress Thermometer score ≥4 (p = 0.012), and bilateral surgery (p = 0.003) predicted moderate-severe pain. The resulting nomogram accurately predicted moderate-severe pain in the validation cohort (AUC =  0.735).

CONCLUSIONS

This nomogram incorporates eight preoperative variables to provide a risk estimate of acute moderate-severe pain following mastectomy. Preoperative risk stratification can identify patients who may benefit from individually tailored perioperative pain management strategies and early postoperative interventions to treat pain and assist with opioid tapering.

Discharge Opioid Prescribing Patterns in an Academic Orthopaedic Setting: Level of Training and Subspecialty Patterns

INTRODUCTION

Despite increased research on opioids in the orthopaedic literature, little is known of the prescribing practices of orthopaedic providers based on their level of training. The purpose of this study was to describe the discharge opioid prescribing patterns of orthopaedic providers, stratifying by level of training and orthopaedic subspecialty, within a single medical system.

METHODS

A retrospective review of orthopaedic surgical encounters was performed over a 1-year period for adults who received a discharge opioid prescription. Patient demographics and prescriber characteristics were collected, including the provider's level of training (attending, fellow, resident, physician assistant [PA], and nurse practitioner [NP]) and surgical subspecialty. Junior residents were postgraduate year 1 to 3, whereas senior residents/fellows were postgraduate year 4 to 6. Discharge opioids were converted to milligram morphine equivalents (MMEs). Overprescribing was defined as a prescribing more than a seven-day supply or >45 MMEs per day. Multivariable linear regression analysis determined the factors associated with discharge MMEs, whereas logistic regression determined the factors associated with overprescribing opioids.

RESULTS

Of the 3,786 patients reviewed, 1,500 met the criteria for inclusion in the study. The greatest proportion of opioid prescriptions was written by junior residents (33.9%), followed by NPs (30.1%), PAs (24.1%), senior residents/fellows (10.6%), and attendings (1.2%). Compared with junior residents, senior residents prescribed -59.4 MMEs, NPs prescribed +104 MMEs, and attendings prescribed +168 MMEs (P < 0.05), whereas PAs prescribed similar amounts (P > 0.05). Orthopaedic subspecialty was also predictive of discharge MMEs (P < 0.05). Senior residents and attendings were more likely to prescribe more than seven days of opioids (P < 0.05), whereas NPs and PAs were more likely to prescribe >45 MMEs per day (P < 0.05).

DISCUSSION

This study demonstrates significant variability in opioid prescribing practices according to provider level of training and subspecialty. National guidelines for opioid prescribing practices and educational programs may help reduce such variability.

LEVEL OF EVIDENCE

Level III, retrospective cohort study.